Intelligent Video Processing Apparatus

ABSTRACT

A camera includes an image processor configured to generate an image or a video data, an intelligent processor configured to perform intelligent analysis and to process on the image or the video data, and a communications interface configured to receive, from an external device, configuration information for the camera, where the configuration information extends a function of the camera.

CROSS-REFERENCE TO RELATED APPLICATIONS

This is a continuation of U.S. patent application Ser. No. 17/010,158filed on Sep. 2, 2020, which is a continuation of International PatentApplication No. PCT/CN2019/074774 filed on Feb. 11, 2019, which claimspriority to Chinese Patent Application No. 201810258526.8 filed on Mar.27, 2018. All of the aforementioned patent applications are herebyincorporated by reference in their entireties.

TECHNICAL FIELD

The present disclosure relates to the video surveillance field, and inparticular, to a definable intelligent video processing apparatus.

BACKGROUND

Currently, with development of video surveillance technologies,surveillance develops from simple video recording to intelligence. Thistrend of intelligence also significantly affects development offront-end cameras. Currently, cameras present a trend of increasingintelligence. In addition, based on rapid development of technologiessuch as computer vision and deep learning in recent years, intelligentcameras have surpassed human beings in accuracy of automaticrecognition. With application of the intelligent cameras, surveillanceefficiency is improved, and labor costs are greatly reduced, therebyessentially promoting modernization and intelligence progresses such asa safe city and a smart city.

Although current intelligent cameras can implement some intelligentanalysis functions, manufacturers usually need to develop differenttypes of intelligent cameras for different application scenarios, andimplemented intelligent analysis functions are also different.Algorithms used for different application scenarios are different, andmanufacturers provide implementation methods only of their own.Therefore, these intelligent cameras usually cannot be used universally.Due to this incompatibility, users need to purchase corresponding typesof intelligent cameras for different application scenarios, therebyincreasing burden of the users.

SUMMARY

An embodiment of the present disclosure provides a definable intelligentvideo processing apparatus. On a basis of an intelligent analysisfunction of a conventional intelligent video processing apparatus, theintelligent video processing apparatus can further allow a user todevelop and extend software and/or hardware for functions of theintelligent video processing apparatus according to a requirement of anactual application scenario, to improve universality of the intelligentvideo processing apparatus and extend application scenarios of theintelligent video processing apparatus.

To achieve the foregoing objective, the intelligent video processingapparatus provided in this embodiment of the present disclosure includesan image obtaining module configured to receive image or video data, anintelligent module, connected to the image obtaining module andconfigured to perform intelligent analysis and processing on theobtained image or video data, and a communications module configured tocommunicate with an external device, where the communications module mayreceive, from the external device, configuration information for theintelligent video processing apparatus, and the configurationinformation is used to extend functions of the intelligent videoprocessing apparatus. The intelligent video processing apparatusprovided in this embodiment of the present disclosure can receive theconfiguration information for the apparatus from the external device,and perform corresponding operations based on the received configurationinformation to implement different functions. A user or a manufacturercan write different configuration information into the intelligent videoprocessing apparatus according to a requirement of an applicationscenario. This improves universality of the intelligent video processingapparatus, and avoids developing different video processing apparatusesbased on different application scenarios.

The configuration information may include at least one of a deeplearning-based neural network model, intelligent video analysisalgorithm code applicable to a specific application scenario, locationtopology information and control information for multi-cameracooperation, a security control list, and a control action indication. Auser or a manufacturer may select to-be-written configurationinformation according to a requirement of a scenario. Configurationinformation supported by the intelligent video processing apparatusprovided in this embodiment of the present disclosure is not limited tothe foregoing listed types.

The communications module in the intelligent video processing apparatusprovided in this embodiment of the present disclosure may be at leastone of a wireless communications module and a fixed communicationsmodule, and a suitable communication mode may be flexibly selectedaccording to a requirement of an application scenario.

In a possible implementation, the intelligent video processing apparatusfurther includes a security and management module configured to managedata and system security of the intelligent video processing apparatus.The security and management module stores a security control list. Thesecurity control list is a management list of the intelligent videoprocessing apparatus for external devices, and includes informationabout an external device allowed to access system data of theintelligent video processing apparatus. At least one security controlpoint is set in a data transmission path of the intelligent videoprocessing apparatus, to perform authentication on transmitted data.With the setting of the security control list and the security controlpoint, authentication may be performed on data to be transmitted to anexternal device and an external operation on a system, to prevent datafrom being transmitted to an unauthorized device or prevent theintelligent video processing apparatus from being illegally hijacked.

In a possible implementation, the intelligent video processing apparatusprovided in the present disclosure may further support extension of anew hardware module as required. The intelligent video processingapparatus includes an extension interface configured to connect at leastone extension module and implement communication between the intelligentvideo processing apparatus and the extension module. Duplexcommunication and control may be implemented between the intelligentvideo processing apparatus and the extension module. The extensionmodule may be a new communications module, a new storage module, or anew intelligent module. The extension module may be selected accordingto a requirement of an actual scenario. With the setting of theextension interface, the intelligent video processing apparatus cansupport extension of a new module. This improves performance of theintelligent video processing apparatus such that the intelligent videoprocessing apparatus can implement more different scenarios.

In a possible implementation, a hardware/software driver of the at leastone extension module is installed in a system of the intelligent videoprocessing apparatus such that the extension module becomes a part ofthe intelligent video processing apparatus.

In a possible implementation, an application programming interface (API)layer is provided on the intelligent video processing apparatus. Thehardware/software driver of the extension module is adapted in the APIlayer such that the extension module can access the intelligent videoprocessing apparatus and/or control another extension module.

In a possible implementation, the extension module stores algorithm codedeveloped for a specific video surveillance scenario. On a basis of anoriginal intelligent video processing apparatus, corresponding extensionmodules are added for different surveillance scenarios. This improvesuniversality of the intelligent video processing apparatus, without aneed of developing different types of intelligent video processingapparatuses for different surveillance scenarios, and therefore cansignificantly reduce development costs.

In a possible implementation, the image obtaining module in theintelligent video processing apparatus includes a lens, an imagecollection module, and an image processing module. In this case, theintelligent video processing apparatus is an intelligent camera.Compared with a conventional camera, the intelligent camera is definableand extensible, and new functions may be extended based on differentapplication scenarios.

The intelligent video processing apparatus provided in this embodimentof the present disclosure allows a user to input different configurationinformation as required, and supports extension of a new hardwaremodule. According to the intelligent video processing apparatus providedin this embodiment of the present disclosure, on a basis of implementinga basic intelligent analysis function, another function can be extendedaccording to a specific requirement of a user, and a plurality of newhardware modules can be extended as required, thereby providing an openand extensible intelligent video processing apparatus. Therefore, a usercan autonomously develop an intelligent analysis application accordingto a specific requirement, and choose to extend new modules based ondifferent application scenarios. This improves compatibility of theintelligent video processing apparatus and enlarges an application scopeof the apparatus.

These aspects or other aspects of the present disclosure are clearer andmore comprehensible in descriptions of the following embodiments.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic structural diagram of a possible intelligent videoprocessing apparatus according to an embodiment of the presentdisclosure,

FIG. 2 is a schematic structural diagram of another possible intelligentvideo processing apparatus according to an embodiment of the presentdisclosure,

FIG. 3 is a schematic diagram of a system architecture of an intelligentmodule according to an embodiment of the present disclosure,

FIG. 4 is a schematic diagram of a connection between an intelligentvideo processing apparatus and an extension module according to anembodiment of the present disclosure,

FIG. 5 is a schematic diagram of another connection between anintelligent video processing apparatus and an extension module accordingto an embodiment of the present disclosure,

FIG. 6 is a schematic diagram of another connection between anintelligent video processing apparatus and an extension module accordingto an embodiment of the present disclosure,

FIG. 7 is a schematic diagram of another connection between anintelligent video processing apparatus and an extension module accordingto an embodiment of the present disclosure,

FIG. 8 is a possible working flowchart of an intelligent videoprocessing apparatus according to an embodiment of the presentdisclosure,

FIG. 9 is an application scenario of an intelligent video processingapparatus according to an embodiment of the present disclosure,

FIG. 10 is another application scenario of an intelligent videoprocessing apparatus according to an embodiment of the presentdisclosure,

FIG. 11 is another application scenario of an intelligent videoprocessing apparatus according to an embodiment of the presentdisclosure,

FIG. 12 is a codec scheme according to an embodiment of the presentdisclosure,

FIG. 13 is another codec scheme according to an embodiment of thepresent disclosure, and

FIG. 14 is a schematic diagram of a control point in an intelligentvideo processing apparatus according to an embodiment of the presentdisclosure.

DESCRIPTION OF EMBODIMENTS

The following describes the technical solutions in the embodiments ofthe present disclosure with reference to the accompanying drawings inthe embodiments of the present disclosure. A specific operation methodin a method embodiment may also be applied to an apparatus embodiment.

Currently, video surveillance is widely applied to industrial, security,daily life, and other fields, and video surveillance cameras areconstantly developing towards intelligence. Currently, an intelligentcamera is applicable only to a specific application scenario, and theintelligent camera is also developed for a specific purpose. Intelligentcameras with different functions need to be implemented for differentsurveillance scenarios, but cannot be used universally, therebyresulting in incompatibility. In this case, development costs ofintelligent cameras are huge, and developed intelligent cameras areincompatible. Therefore, to resolve problems, such as incompatibilityand a limited computing capability, of an existing intelligent camera,an embodiment of this application provides a definable intelligent videoprocessing apparatus, allowing a user to develop and extend softwareand/or hardware for functions of the intelligent video processingapparatus according to a requirement of an actual application scenarioin order to improve universality of the intelligent video processingapparatus.

FIG. 1 is a schematic structural diagram of a possible intelligent videoprocessing apparatus according to an embodiment of the presentdisclosure. The intelligent video processing apparatus includes an imageobtaining module 110, an intelligent module 120, and a communicationsmodule 170. Other modules or components are optional in this embodimentof the present disclosure.

The image obtaining module 110 in the intelligent video processingapparatus 100 provided in this embodiment of the present disclosure isconfigured to obtain image and/or video data for processing and analysisby the intelligent video processing apparatus. A manner of obtaining animage by the image obtaining module 110 varies based on differentapplication scenarios. In a scenario, the intelligent video processingapparatus 100 may be connected to various different front-end devices. Afront-end device may transmit collected image/video data to theintelligent video processing apparatus 100 for further analysis andprocessing. In this case, a physical form of the image obtaining module110 may be an interface connected to the front-end device. The followingprovides several specific application scenarios of the intelligent videoprocessing apparatus 100 provided in this embodiment of the presentdisclosure.

Scenario 1: In some application scenarios of an access control camera,an access control system also needs to have functions such as facedetection and alarms. In this case, based on different accuracy andtarget scopes required for detection, a corresponding intelligent videoprocessing apparatus 100 may be provided, and targeted applicationdevelopment is performed. In this case, the access control camera andthe corresponding intelligent video processing apparatus 100 arecombined into an intelligent access control system that can implementmore functions.

Scenario 2: The intelligent video processing apparatus 100 is externallyconnected to a mobile phone terminal. As a front-end image/videoobtaining device, the mobile phone terminal cooperates with theintelligent video processing apparatus 100 to form an intelligentsurveillance system with a larger capacity and capable of real-timerecording and analysis. Flexibility of obtaining an image/video by theintelligent video processing system together with the mobile phonegreatly extends application scenarios of intelligent video surveillance.

Scenario 3: A special front-end device is usually applicable tosurveillance in a specific scenario, and has a specific sensor (a smoke,infrared, humidity, or black light sensor, or the like) and functionssuch as vibration and audible and visual alarms. According to arequirement of public security or another application scenario, thespecial front-end device is connected to the intelligent videoprocessing apparatus 100, and a corresponding application is developed,to implement rapid local analysis by the special front-end device. Thespecial front-end device and the intelligent video processing apparatus100 together form an intelligent front-end video analysis system.

In the foregoing scenarios, an interface for connecting the front-enddevice to the intelligent video processing apparatus 100 may be in awired or wireless communication mode. The wired mode may include a modesuch as a Transmission Control Protocol (TCP)/Internet Protocol (IP)communications technology or a User Datagram Protocol (UDP) technologyof Ethernet technologies, a standard Universal Serial Bus (USB) port orComponent Object Model (COM) interface, or another similar standardport. The wireless communication mode may include technologies such asWi-Fi, BLUETOOTH, ZIGBEE, or ultra-wideband (UWB). A correspondingconnection mode may be selected based on an actual application scenarioand a hardware form of the front-end device.

In another application scenario, a lens is disposed on the intelligentvideo processing apparatus 100 to collect image and/or video data. Inthis case, the image obtaining module 110 may be a collective name ofthe lens, an image collection module, and an image processing module. Inthis case, the intelligent video processing apparatus is presented as aspecial definable intelligent camera. FIG. 2 is a schematic structuraldiagram of a definable intelligent camera 200 according to an embodimentof the present disclosure. The intelligent camera 200 integrates acommon camera for directly collecting image and/or video data with theintelligent video processing apparatus 100, to form the definableintelligent camera 200 that can not only collect image/video data andintelligently process video data, but also support voluntarily definingan intelligent analysis algorithm according to an actual requirement.The definable intelligent camera 200 provided in this embodiment of thepresent disclosure is a combination of an existing common camera and theintelligent video processing apparatus 100. Main components of thedefinable intelligent camera 200 are basically similar to those of theintelligent video processing apparatus 100. Three components, that is, alens A, an image collection module 210, and an image processing module220, correspond to the image obtaining module 110 in the intelligentvideo processing apparatus 100, and are configured to collect imageand/or video data. The lens A may be of a fixed-aperture, auto-iris,auto-zoom, or the like. The image collection module 210 is configured torecord a captured optical signal. The image collection module 210 isusually any type of optical sensor, for example, a complementarymetal-oxide-semiconductor (CMOS), a charge-coupled device (CCD), or adevice implementing a similar function.

Optionally, in some scenarios, the image collection module 210 collectsan unprocessed video stream, and needs to use the image processingmodule 220 to process the video stream. The image processing module 220usually has functions such as analog-to-digital (A/D) conversion, signalprocessing, and image zooming. A/D conversion and signal processingtechnologies are well-known by a skilled person. In some embodiments,for example, when the video collection module 210 in the intelligentcamera 200 is the CMOS sensor, the video collection module can implementthe A/D conversion function. Therefore, the image processing module 220does not need to have an A/D conversion function. A result obtainedthrough A/D conversion and signal processing is digital image data.According to an embodiment, before the digital image data is sent to anintelligent module 230, the video and image processing module 220processes the digital image data to obtain at least one image with aspecific size. In another embodiment, no zooming or size adjustmentneeds to be performed on an image and/or a video from a front end.

The intelligent module 120 in the intelligent video processing apparatus100 provided in this embodiment of the present disclosure is mainlyconfigured to perform intelligent analysis and processing on receivedvideo or image data, and manage and control other modules in theintelligent video processing apparatus 100. The intelligent module 120may perform a corresponding operation and implement a correspondingfunction based on configuration information sent from the outside.

The intelligent analysis and processing performed by the intelligentmodule 120 can generate a complete determining result of an abnormalevent that occurs in a monitored scenario. Another back-end device of avideo surveillance system does not need to perform post-processing onthe complete determining result. The complete determining result canprovide complete information related to the abnormal event. Theintelligent module 120 processes and analyzes a video at a front end,thereby processing the video in a more timely manner. In addition, thisavoids transmitting all video data to a back-end device for processing,thereby saving bandwidth.

The intelligent module 120 may be a processor or a controller, forexample, may be a central processing unit (CPU), a general purposeprocessor, an artificial intelligence (AI) chip, a graphics processingunit (GPU), a digital signal processor (DSP), an application-specificintegrated circuit (ASIC), a field-programmable gate array (FPGA) oranother programmable logic device, a transistor logic device, a hardwarecomponent, or any combination thereof. The processor may bealternatively a combination that implements a computing function and/ora control function. For example, the processor includes a combination ofone or more microprocessors, a combination of a DSP and amicroprocessor, or a combination of a CPU and a GPU or an AI chip.

The communications module 170 is configured to receive, from an externaldevice definition content, namely, configuration information for theintelligent video processing apparatus 100, and is further configured tosend data of the intelligent video processing apparatus 100 to anexternal device. The configuration information is used to extendfunctions that can be implemented by the intelligent video processingapparatus 100. After receiving the configuration information, theintelligent video processing apparatus 100 may parse the receivedconfiguration information, and perform a corresponding operation basedon content of the configuration information to implement a function ofthe configuration information. The configuration information herein mayinclude intelligent video analysis software or algorithm code developedfor various video surveillance application scenarios, or may include adeep learning-based neural network model, or an algorithm and controlinformation that require multi-camera cooperation in some applicationscenarios, or may be control information or the like for internal datasecurity of the intelligent video processing apparatus 100.

A user or a device manufacturer may write, from the communicationsmodule 170 into the intelligent video processing apparatus, videoprocessing software or a video processing algorithm that is developedbased on a specific application scenario, or other control informationsuch that the intelligent video processing apparatus can meet arequirement of the application scenario, thereby implementing functionextensibility of the intelligent video processing apparatus.

The communications module 170 may also be configured to warn and notifya remote user of some key recognition results of the intelligent videoprocessing apparatus 100 in a timely manner, including triggering anshort message service (SMS) message, or triggering some necessarycamera-network cooperation actions such as authentication on a riskyoperation.

The communications module 170 in this embodiment of the presentdisclosure may be a wireless communications module, including asignaling-plane protocol stack for transmitting signaling and auser-plane protocol stack for transmitting data. The communicationsmodule 170 in this embodiment of the present disclosure may bealternatively a fixed communications module, including a management portfor transmitting control information and a data transfer port fortransmitting data.

In a specific implementation, the wireless communications module may bea Wi-Fi chip, a ZIGBEE chip, a BLUETOOTH chip, or a baseband chipsupporting second generation (2G)/third generation (3G)/fourthgeneration (4G)/fifth generation (5G), and the fixed communicationsmodule may be a component supporting an asymmetric digital subscriberline (ADSL), an x passive optical network (xPON), a packet transportnetwork (PTN), or another wired access technology. With networkevolution and technology development, another access mode may alsoemerge. The wireless communications module or the fixed communicationsmodule may be a component supporting the other access mode. This is notlimited herein. The communications module 170 in the intelligent videoprocessing apparatus 100 may be selected according to a requirement ofan application scenario. A wireless communications module, or a fixedcommunications module, or both a wireless communications module and afixed communications module may be installed on the intelligent videoprocessing apparatus 100.

Optionally, the intelligent video processing apparatus 100 provided inthis embodiment of the present disclosure may further include a codecmodule 150. The codec module 150 may be configured to encode the digitalimage data into any one of a plurality of known formats for a continuousvideo sequence, a limited video sequence, a static image, or animage/video stream. For example, image information may be encoded into aMoving Picture Experts Group (MPEG)1, MPEG2, MPEG4, Joint PhotographicExperts Group (JPEG), or Motion JPEG (MJPG) format, or a bitmap, andthen transmitted out. The codec module 150 is further configured toperform channel error correction encoding and decoding on data incommunication with an external device, to reduce a bit error rate anddata errors. The codec module 150 may be further configured to performfeedback encoding based on a network quality condition (bandwidth, ajitter, a latency, or the like) of an output interface, and canadaptively select a suitable encoding scheme based on current networkquality. Optionally, a codec function may be alternatively integrated inthe intelligent module 120.

Optionally, the intelligent video processing apparatus 100 provided inthis embodiment of the present disclosure may further include a storagemodule 130 configured to store program code that needs to be executed bythe intelligent video processing apparatus 100 to perform intelligentanalysis, and received video or image data. According to a requirementof an actual application scenario, the storage module 130 in theintelligent video processing apparatus 100 provided in this embodimentof the present disclosure is extensible. At least one storage module maybe extended through an extension interface a as required. The memory 130may be a read-only memory (ROM), another type of static storage devicethat can store static information and an instruction, a random-accessmemory (RAM), another type of dynamic storage device that can storeinformation and an instruction, an electrically erasable programmableROM (EEPROM), a compact disc (CD) ROM (CD-ROM), another optical discstorage, an optical disc storage (including a compact optical disc, alaser disc, an optical disc, a digital versatile disc (DVD), a BLU-RAYDISC, and the like), a magnetic disk storage medium, another magneticstorage device, or any other medium that can carry or store expectedprogram code in an instruction or data structure form and can beaccessed by a computer. However, this application is not limitedthereto.

Different from an existing intelligent video analysis device, theintelligent video processing apparatus 100 provided in this embodimentof the present disclosure is definable and extensible. Scenarios inactual application vary greatly, and required video processing alsovaries. The intelligent video processing apparatus in this embodiment ofthe present disclosure can support re-defining the intelligent videoprocessing apparatus, but is not limited to a specific applicationscenario. A device manufacturer or a user may write, into theintelligent video processing apparatus 100 using the communicationsmodule 170, an application or an algorithm customized for a specificapplication scenario.

To make the intelligent video processing apparatus 100 provided in thisembodiment of the present disclosure definable, an embodiment of thisapplication provides a definable intelligent module 120. As shown inFIG. 3, the intelligent module 120 in this embodiment of the presentdisclosure may be divided into four layers from hardware to software anintelligent module hardware layer 121, a driver layer 122, a softwarescheduling layer 123, and a definable software and algorithm layer 124.

The intelligent module hardware layer 121 is a hardware entity of theintelligent module 120. As mentioned above, a most basic function of theintelligent module 120 is to implement computing and control functions,and may be implemented by different hardware, for example, a CPU, a DSP,an ASIC, or an FPGA. Flexible selection may be performed according to arequirement of an actual scenario.

A corresponding driver needs to be installed such that the intelligentmodule 120 can be connected to a system of the intelligent videoprocessing apparatus 100 and operate properly. The driver layer 122includes all drivers required for supporting a connection of theintelligent module 120 to the system of the intelligent video processingapparatus 100 and ensuring proper operating of the intelligent module120. After the corresponding driver is installed, the system may controland invoke the intelligent module 120, to implement a function of theintelligent module 120.

The software scheduling layer 123 is configured to during operating ofthe intelligent module 120, implement coordination and invocationbetween various programs running on the intelligent module 120. In someapplication scenarios, a plurality of programs may run, but theintelligent module 120 has limited operation resources. Therefore, thesoftware scheduling layer 123 needs to coordinate a running sequence ofthe programs.

The definable software and algorithm layer 124 is a collective name ofexecutable software and algorithms in the intelligent module 120. A usermay write corresponding software and algorithms into the intelligentmodule 120 based on different application scenarios. In addition, mutualinvocation between application software or algorithms at the definablesoftware and algorithm layer 124 is further supported. To be specific,software or an algorithm may release a function block that can beimplemented by the software or the algorithm, and other software oralgorithms may use the function block released by the software or thealgorithm. This invocation mechanism of application software andalgorithms enables a user to conveniently replace a software or analgorithm at the definable software and algorithm layer based on anapplication scenario.

With the setting of the foregoing four layers, the intelligent videoprocessing apparatus 100 can be definable. Required configurationinformation may be written into the intelligent video processingapparatus 100 based on different application scenarios, therebyextending universality and an application scope of the intelligent videoprocessing apparatus 100.

An extension interface a is further disposed in the intelligent videoprocessing apparatus 100 provided in this embodiment of the presentdisclosure. When a hardware capability of the intelligent videoprocessing apparatus 100 is insufficient to meet a requirement of anapplication scenario, a user may extend a new hardware module for theintelligent video processing apparatus 100 using the extension interfacea to meet a computing requirement. An extension module in thisembodiment of the present disclosure may be a new communications module,a new storage module, a new intelligent module, or the like.

In some scenarios, a communications module in an original intelligentvideo processing apparatus may support only wired communication. Whencommunication in a wired communications network is congested orinterrupted, a new communications module may be extended using theextension interface. The extended communications module is acommunications module supporting wireless communication. Further, theextended communications module may support a communication mode such asWi-Fi communication, ZIGBEE communication, BLUETOOTH communication, or2G/3G/4G/5G.

In some scenarios, an intelligent video processing apparatus needs tostore more image data, but an original intelligent video processingapparatus is unable to support this requirement. In this case, morestorage modules may be extended using the extension interface to improvea storage capability of the intelligent video processing apparatus. Anextended storage module may be a ROM, another type of static storagedevice that can store static information and an instruction, a RAM,another type of dynamic storage device that can store information and aninstruction, an EEPROM, a CD-ROM, another optical disc storage, anoptical disc storage (including a compact optical disc, a laser disc, anoptical disc, a DVD, a BLU-RAY DISC, and the like), a magnetic diskstorage medium, another magnetic storage device, or any other mediumthat can carry or store expected program code in an instruction or datastructure form and can be accessed by a computer. However, thisapplication is not limited thereto.

In some other application scenarios, an extension module 12N may be anintelligent module that stores an application or an algorithm developedfor a specific application scenario. An intelligent video processingapparatus 100 on which the extension module is installed is applicableto the corresponding specific application scenario, without a need ofsecondary development. Alternatively, the extension module may be simplya module providing a computing capability for the intelligent videoprocessing apparatus 100, and performs computing under control of theintelligent module 120. Regardless of which type of intelligent moduleis extended, a user may perform secondary development on the intelligentvideo processing apparatus 100 using the communications module 170 suchthat the intelligent module 120 and the extension module 12N complete anapplication or computing that is defined by the user. Optionally, theextended module may be an embedded microprocessor, a general purposeprocessor, a DSP, an ASIC, an FPGA or another programmable logic device,a transistor logic device, or a hardware component, or may be an AIchip, a GPU, or another intelligent processor, or may be any combinationof the foregoing components.

In terms of control, the intelligent module 120 in the intelligent videoprocessing apparatus 100 provided in this embodiment of the presentdisclosure controls other modules. Alternatively, optionally, after anextension module is added, after authorization by the intelligent videoprocessing apparatus 100, one extension module 12N may control othermodules. According to this embodiment of the present disclosure, bydisposing a relay station (for example, a hub) in the extension module12N, the extension module 12N can be used as a part of the entireintelligent video processing apparatus 100, but not merely as aperipheral component of the intelligent video processing apparatus 100.

In terms of software/hardware installation and connections, a specificstandard and/or protocol may be used for the intelligent videoprocessing apparatus 100 provided in this embodiment of the presentdisclosure, to install the extension module 12N on the intelligent videoprocessing apparatus 100. Further, an API layer is provided on theintelligent video processing apparatus 100. A hardware/software driverof the new extension module 12N is installed at the API layer in thesystem of the intelligent video processing apparatus 100, to implementcontrol of the intelligent module 120 on the extension module 12N andmutual data transmission. In addition, the extension module mayalternatively access the intelligent module 120 using software andcontrol the entire system of the intelligent video processing apparatus100. The extension interface a in the intelligent video processingapparatus 100 is configured to provide a connection interface for theextension module 12N and the intelligent video processing apparatus 100such that the intelligent video processing apparatus 100 can communicatewith the extension module 12N using the extension interface a. In termsof a hardware interface, the extension interface a may be in a wired orwireless form, and may be disposed separately, or may be integrated inthe communications module 170. The extension interface a may use atechnology such as TCP/IP or UDP, or may be a standard file transferinterface, for example, an integrated drive electronics (IDE),Peripheral Component Interconnect (PCI)/PCI Express (PCI-E), SmallComputer System Interface (SCSI), USB, or Serial Advanced TechnologyAttachment (SATA) interface, or may use a wireless communicationstechnology such as WI-FI, ZIGBEE, or BLUETOOTH. Flexible selection maybe performed based on different application scenarios. This is notlimited herein in the present disclosure.

In terms of a power supply, the extension module 12N may be powered bythe intelligent video processing apparatus 100, or may be powered by anextension module with a power supply function. In addition, all modules(including the extension module 12N) may have a standby function, andthe intelligent module 120 may alternatively control a power supply forother modules (including the extension module 12N). A driver installedin the system of the intelligent video processing apparatus may includepower supply control information of the extension module 12N.

In addition, the intelligent video processing apparatus 100 provided inthis embodiment of the present disclosure can allocate a requiredintelligent analysis function to an extended module for implementation.This maximally relieves computing pressure of the intelligent videoprocessing apparatus 100 such that a basic function and hardware of theintelligent video processing apparatus 100 are greatly simplified, and asize of the intelligent video processing apparatus 100 can be reduced.

The following provides some examples of the definable intelligent camera200 and the intelligent video processing apparatus 100 provided in theembodiments of the present disclosure, to further illustrate features ofthe present disclosure. A mode of a connection between the intelligentvideo processing apparatus and an extension module is mainly shown.

Example 1

FIG. 4 shows a data transmission mode and a module control method inwhich a TCP/IP communications technology of Ethernet technologies isused. As shown in FIG. 4, data is transmitted between the intelligentvideo processing apparatus 100 and the extension module 12N using theTCP/IP technology of Ethernet technologies. In addition, using a hub inthe extension module 12N, the extension module 12N may be used as a nodein the intelligent camera 200 or the intelligent video processingapparatus 100. This can implement a free connection between extensionmodules.

As shown in FIG. 4, the extension interface a on the intelligent videoprocessing apparatus 100 has several interface layers, including an APIlayer. When a new extension module 12N is connected, using the APIlayer, the intelligent video processing apparatus 100 receives aninstallation program for the extension module using an Ethernettransmission technology, identifies the extension module 12N, andinstalls a driver of the extension module 12N in the system of theintelligent video processing apparatus such that the intelligent modulecan control the extension module 12N. Moreover, in addition to theTCP/IP technology, data transmission between the intelligent videoprocessing apparatus 100 and the extension module 12N may bealternatively implemented using another technology such as a UDPtechnology.

Example 2

FIG. 5 shows a method for implementing data transmission and modulecontrol between the intelligent video processing apparatus 100 and theextension module 12N using a standard USB port. As shown in FIG. 5, theextension interface a on the intelligent video processing apparatus 100has several interface layers, including an operating system (OS)/Coreinterface layer. A USB chip driver is pre-installed at the OS/Coreinterface layer, and a USB chip is disposed in the extension module.Therefore, when a new extension module 12N is connected, the intelligentvideo processing apparatus 100 identifies and drives a USB chip in theextension module 12N using a USB chip driver at the OS/Core interfacelayer, converts data of the extension module into data that can beidentified by the intelligent video processing apparatus 100, andreceives a data stream from the extension module 12N and/or sends datato the extension module, to control the extension module. In addition,using a hub in the extension module 12N, the extension module 12N may beused as a node in the intelligent video processing apparatus 100. Thiscan implement a free connection between extension modules. In additionto the standard USB port, data transmission between the intelligentvideo processing apparatus 100 and the extended module 12N may bealternatively implemented using another standard port with a similarchip.

Example 3

FIG. 6 shows an implementation of a connection between the intelligentvideo processing apparatus 100 and the extension module 12N using awireless connection technology. As shown in FIG. 6, a wireless powerinterconnection interface and an access port are disposed in theintelligent video processing apparatus 100, and a wireless powerinterconnection interface, a client, and a receiver are disposed in theextension module 12N. When the extension module 12N is connected to theintelligent video processing apparatus 100, the intelligent videoprocessing apparatus 100 powers the extension module using the receiverof the extension module 12N. The extension module 12N may serve as apower supply receiver, or may serve as a wireless power supplytransmitter, to implement a wireless power supply.

For data transmission, the intelligent video processing apparatus 100has the access port, the extension module 12N has the clientcorresponding to the access port, and data transmission is implementedthrough a connection between the access port and the client. Inaddition, an access port on the extension module 12N may be connected toa client on another extension module to implement data transmissionbetween the extension modules. In the present disclosure, wirelessconnection technologies may further include technologies such as WI-FI,BLUETOOTH, Infrared Data Association (IrDA), ZIGBEE, and UWB.

Example 4

FIG. 7 shows an implementation of a cascading system architecture ofextension modules using a new technology (for example, a Thunderbolttechnology). As shown in FIG. 7, provided that the intelligent module120 serving as a control module transmits data through a PCI-E bus,internal data processing transmission of other modules (for example, thestorage module 130 and the code module 150) in the intelligent videoprocessing apparatus 100 is all performed through the PCI-E bus. Usingthe Thunderbolt technology and a corresponding interface, the extensionmodule 12N may be connected to the intelligent module 120, and extensionmodules may also be connected to each other using the Thunderbolttechnology.

The intelligent video processing apparatus 100 and the definableintelligent camera 200 provided in the embodiments of the presentdisclosure further include a power supply determining mechanism for anew extension module 12N. Power consumption information in a deviceidentifier (ID) of the new extension module 12N is identified todetermine that the intelligent video processing apparatus or anotherextension module connected to the new extension module 12N is to supplypower. FIG. 8 shows a process of identifying a device ID of a newextension module 12N connected to the extensible intelligent camera orthe intelligent video processing apparatus.

As shown in FIG. 8, when a connection needs to be established to a newextension module 12N, the intelligent video processing apparatusidentifies a hardware ID of the extension module 12N and establishescommunication with the extension module. Then a system (a system of theextensible intelligent camera or the intelligent video processingapparatus, similarly hereinafter) is searched for a registered driver,and the registered driver is compared with a driver of the extensionmodule 12N, to confirm whether the extension module 12N is a newextension module. If the extension module 12N is not a new extensionmodule, the registered driver is installed on the extension module 12N,to start the extension module 12N and end the current connectionoperation. If the extension module 12N is a new extension module,communication with the new extension module 12N is established, andinformation (for example, power information) of the new extension module12N is read from the extension module. Then it is determined whetherpower supplied to the new extension module 12N is sufficient for theintelligent video processing apparatus or another extension module thatis connected to the new extension module. If the power supply isinsufficient, the system cancels the connection to the new extensionmodule 12N, prompts the new extension module 12N to connect to a powersupply, and then end the current connection operation. If the powersupply is sufficient, the system looks for a driver of the new extensionmodule 12N in a memory of the extension module. In the foregoing steps,if no driver of the new extension module 12N is found, it is promptedthat no driver of the extension module is found. In this case, a usermay download a driver of the extension module from the Internet ormanually install a driver of the extension module 12N, and then installa registered driver on the extension module, to start the extensionmodule 12N and finally end the current connection operation. In theforegoing steps, if a driver of the extension module is found, thesystem automatically downloads and installs the driver of the extensionmodule 12N. In this case, if the new extension module 12N has anoperating system subsystem, application software of the subsystem isinstalled. Finally, the current connection operation is ended.

The foregoing content mainly describes a constituent structure of theintelligent video processing apparatus and the intelligent cameraprovided in the embodiments of the present disclosure, and connectionand operating modes of the extension module 12N and the intelligentvideo processing apparatus 100 or the intelligent camera 200. Thefollowing describes specific application scenarios of the definableintelligent camera and the intelligent video processing apparatusprovided in the embodiments of the present disclosure, to furtherdescribe beneficial effects of the present disclosure.

Application 1: In some scenarios, a snapshot of a target needs to betaken in a linkage manner. When finding and focusing on the target, anintelligent camera with a larger surveillance scope needs to notifyanother intelligent camera around to take a snapshot in a linkagemanner. A rule of a linkage between intelligent cameras may be flexiblyspecified as required, and the linkage rule is written into a definableintelligent camera using a communications module.

FIG. 9 shows functions of apparatuses in the scenario in the application1 and a process of interaction between the apparatuses. When a newdefinable intelligent camera 1 is connected to the system, theintelligent camera 1 notifies a nearby intelligent computing node of itslocation information. The intelligent computing node herein may bedisposed in an intelligent camera or an edge computing node. Afterreceiving the location information of the newly connected intelligentcamera 1, the intelligent computing node calculates a location based onlongitude and latitude coordinate information, and notifies anintelligent camera A with a larger surveillance scope that a targethuman face is recognized in a surveillance area. In this case, theintelligent camera 1 or an intelligent camera 2 is triggered to take asnapshot. The intelligent camera A registers a cooperative snapping ruleand a surveillance area for triggering snapping. When a target humanface is detected, the intelligent camera 1 or 2 is triggered to take asnapshot. If snapped target human faces are a same target, theintelligent camera A denotes them as the same target, and manages atotal quantity of images snapped under triggering and an optimal anglefor snapping. After snapping an image of the human face, the intelligentcamera 1 or 2 uploads the snapped image of the human face and acorresponding ID to the intelligent computing node.

Application 2: In some traffic surveillance scenarios, surveillance onnew traffic violation events in video surveillance area needs to beadded. Therefore, a new traffic rule determining function, andcorresponding event recording and image snapping functions need to beinjected. A user may write an algorithm of a newly implemented functioninto the definable intelligent camera or the intelligent videoprocessing apparatus using the communications module according to arequirement of an application scenario. In this way, when a new trafficrule is launched, there is no need to replace all surveillance devices,but the new traffic rule is applicable based on the original devices.This can greatly reduce costs.

FIG. 10 shows a process of defining a rule for the intelligent camera inthe application 2 and an operating process of the intelligent camera. Anintelligent computing node writes, into the intelligent camera A, analgorithm corresponding to a defined rule. The intelligent node requiresthat the camera A snaps an image of an action of violating a new parkingrule, that is, notifies the camera A that, a local area of asurveillance image becomes a yellow no-parking area, and the camera Aneeds to identify and snap an image of a vehicle that parks for morethan 10 minutes, and record a time in real time. If the camera A detectsthat its intelligent analysis capability is insufficient, the camera Amay request the intelligent computing node to assist in vehicle licenseplate recognition and computing. The intelligent computing node detectsfor local intelligent modules. If local intelligent modules areinsufficient, more intelligent modules may be extended using theextension interface a. After detecting and snapping an image of avehicle violating regulations, the intelligent camera A uploads theimage and marks a time in real time. After receiving the image, theintelligent computing node recognizes vehicle information such as avehicle license plate, and records a result and a time.

Application 3: A large quantity of requirements such as facialrecognition, vehicle recognition, posture recognition, and behavioranalysis are imposed in current intelligent video surveillancescenarios. Currently, deep learning is usually used to improverecognition and analysis performance. A deep learning algorithm is usedto establish a neural mechanism for simulating analysis and learningperformed by a human brain, construct a network structure model with aplurality of hidden layers, and train a large amount of data to obtainrepresentative feature information in order to implement interpretationand prediction for data such as an image, a voice, or a text, andimprove accuracy of classification prediction. In the image recognitionfield, a deep learning-based model, especially a convolutional neuralnetwork (CNN) model, is widely applied. The deep learning algorithmusually includes three steps: dataset construction, model training andgeneration, and image classification and recognition. A deeplearning-based neural network model is trained and generated based onlearning of a large quantity of image features. A neural network modelwith good performance is established based on a large amount ofappropriate image data. Therefore, a suitable image database first needsto be constructed for the neural network to learn. Model and parametertraining and generation mainly include two processes: training andtesting. A constructed image dataset undergoes data conversion, and thenis input as underlying data of a convolutional neural network. Theconvolutional neural network performs operations such as convolution andpooling on the data to output a network model. A result such as aparameter that describes model performance is observed, and a networkmodel parameter is adjusted. It is learned that the output performanceparameter is converged and tends to be in a stable state. Then the modeltraining ends. Extracted image features are stored in the model. Afterthe model is trained and generated, application performance of the modelneeds to be tested. Pictures may be centrally extracted from testpictures. A trained classification model is invoked to transmit testpicture data through the network model, and finally, a comparison isperformed on classification accuracy of the test data. If precision isrelatively low, it indicates that the network model obtained throughtraining does not reach an expectation, that is, the neural networkparameter for deep learning is not optimal, and the network model needsto be further optimized to improve its test accuracy. There are mainlythe following three methods for optimizing the neural network model: 1.Extend the image dataset for training. 2. Change a network structure ofthe model. 3. Adjust the network parameter of the model. After a neuralnetwork model and parameter with superb performance are obtained, theymay be used in an actual image recognition application. In anapplication stage, first, a target in a surveillance scenario ispreprocessed to extract, as an input of the neural network, featureinformation that can be used for recognition, and operations such asrecognition and classification are performed on the feature informationusing the convolutional neural network model. When performance of thedeep learning algorithm is improved, a required neural network modelneeds to be obtained through an update. A quantity of layers of a deeplearning algorithm is increased from 20 to 30, and a quantity of neuronsat some network layers is increased. A parameter of the deep learningalgorithm is a latest parameter obtained through learning and trainingin various regions. A user may write, into the intelligent videoprocessing apparatus, information such as a neural network model relatedto a video surveillance scenario or a latest deep learning parameter. Ifthe intelligent video processing apparatus has an insufficient computingcapability for the new deep learning algorithm, an intelligent moduleneeds to be added to improve a computing capability of the intelligentvideo processing apparatus in order to meet a computing capabilityrequirement of deep learning. A method for extending a new intelligentmodule has been described above, and details are not described hereinagain.

Application 4: In some scenarios, an error occurs in a fixed network,and image or video data needs to be transmitted in a wireless networkaccess mode. When the fixed network is congested, a parameter isadjusted such that still image information in a surveillance scenario iscompressed with a high compression ratio during encoding, to clearlypresent a changed part.

FIG. 11 shows a working process of adjusting an encoding parameter dueto network congestion in the application 4. If a fixed network iscongested, an intelligent computing node instructs a definableintelligent camera A to upload data through a wireless interface, andstipulates an upload rate. The intelligent camera A adjusts a frame rateaccording to an MPEG principle and based on a codec scheme such asH.264, H.265, or a national or industry standard of China. Further, theintelligent camera A may adjust an encoding parameter, for example,intensify encoding for a non-static area or weaken encoding for a staticbackground area. After encoding is completed, the intelligent camera Aselects a wireless interface for uploading data. Before uploading data,the intelligent camera A may further choose to check a securityparameter, for example, whether a destination address is in a list ofauthorized addresses, and whether encryption is required in transmissionor privacy information needs to be removed in transmission. Afterreceiving the uploaded data, the intelligent computing node performsdecoding and subsequent processing.

Currently, in various encoding algorithms, a video encoding rate may bedynamically adjusted according to the MPEG principle. Two main aspectsmay be combined for improving encoding of video surveillance.

Aspect 1: A static background for video surveillance usually remainsunchanged for a long time. During encoding of this scenario, the staticbackground may be recognized as a long-time static area based oninterframe changes, to reduce a codec rate and highlight a bit rate ofother areas. FIG. 12 shows the working process. When an image encodingblock is input, a background area that is static for a long time isrecognized using an interframe comparison. It is detected whether thereis a static area and no pixel change (or merely a light change) occursin the static area. If there is no static area, encoding is performedaccording to an original encoding scheme. Alternatively, if there is astatic area, a background identifier ID is transferred, and a pixelblock corresponding to background frame is directly extracted in adecoding area. In a scenario with a light change, a background frame anda new ID may be defined every several frames.

Aspect 2: For transmission security, FIG. 13 shows a process of removingprivacy information from a video before transmission without encryption.In some surveillance scenarios, privacy information needs to be removedfrom a video before transmission, for example, in a scenario in whichonly crowd density or whether an old person falls down needs to bemonitored. If a surveillance scenario imposes a requirement for removingprivacy information, a method for removing privacy information isselected, for example, using a thermodynamic diagram without detailedfacial information, or automatically applying mosaics to a face.Finally, an original video is stored locally and is completely sent whena network condition becomes good, privacy information is removed, and avideo is uploaded.

It should be noted that although the embodiments of the presentdisclosure describe how to use the definable intelligent camera A andthe definable intelligent camera 1 or 2 in the foregoing applicationscenarios, functions of these intelligent cameras may be alternativelyimplemented by a combination of a common camera and the intelligentvideo processing apparatus.

In an optional manner, a management and security module 160 is furtherdisposed in the intelligent video processing apparatus 100 provided inthis embodiment of the present disclosure. The management and securitymodule 160 is configured to manage data security of the intelligentvideo processing apparatus 100, to prevent Internet hackers fromattacking the intelligent video processing apparatus 100 to obtainimage/video data or an intelligent analysis result. The management andsecurity module 160 may be an independent hardware entity.Alternatively, a function of the management and security module 160 maybe integrated in the intelligent module 120 or an extension module. Inthis case, the management and security module 160 merely serves as alogical component, but not an independent hardware entity.

To prevent attacks from Internet hackers, a security control list and asecurity control point are added in this embodiment of the presentdisclosure, and remote setting or secondary authentication and licensingmay be performed using signaling of a wireless network or a managementplane of a fixed network. In this embodiment of the present disclosure,a control stream received by the communications module is used tocontrol a destination address list of a data stream such that the datastream is not transmitted to an address for illegal attacking. Themanagement and security module 160 may store the security control list,to manage a data flow direction of the intelligent video processingapparatus 100, perform authentication-related key computing, and thelike.

In this embodiment of the present disclosure, the security control listis a management list of the system for external devices. The list mayinclude an external device allowed to access system data, or a deviceallowed to invoke system hardware, or a system-allowed destinationaddress for data sending. The security control list may record anyinformation that can represent an identity of an external device, forexample, a media access control (MAC) address or an IP address of theexternal device, or another number according to a related standard of acountry.

The security control point is a node selected in a data transmissionpath in the system of the intelligent video processing apparatus 100.The node manages data or control information passing the node, anddetermines whether transmitted data conforms to system-stipulatedsecurity. Authentication and control are two main operations performedby the system at the security control point. A user may define,according to an actual requirement, a quantity of security controlpoints and operations that need to be performed at the security controlpoints.

The security control list may be set in at least one of a list oflicensed addresses is written from the communications module to theintelligent video processing apparatus, a password/key/mechanism forauthentication is written from the communications module, and localverification is performed, where the verification process may beperformed by the management and security module 160, and when necessary,the intelligent module 120 may perform a complex security operationseparately or together with the management and security module 160, or adevice requesting a connection may read data from the communicationsmodule only after licensing, where the communications module may performexternal secondary authentication, or an administrator may performlicensing and confirmation.

As shown in FIG. 14, two security control points are set in the systemof the intelligent video processing apparatus 100. Using a control pointX1 as an example, the following describes functions that can beimplemented by the security control points and their working modes.

The system mainly performs two operations at the control point X1authentication and control. When a data stream passes the control pointX1, a destination address of the data stream may be obtained at thecontrol point X1, and it is determined whether the data stream needs tobe transmitted, whether the data stream needs to be encrypted fortransmission, and whether to select wired transmission or wirelesstransmission. In addition, the security control list may be furthersearched for the destination address of the data stream to determinewhether authentication succeeds. If the destination address is notrecorded in the security control list or is recorded in a securitycontrol list that is a transmission-prohibited list, the communicationsmodule may perform external secondary authentication, or an operator mayperform licensing and confirmation. Setting an authentication step fordata stream transmission can maximally prevent a data stream from beingtransmitted to an unauthorized destination address, thereby improvingdata security.

The system may further control and manage other modules in the system atthe control point X1. For example, when receiving external configurationinformation from the communications module, the control point X1 maynotify other modules of a working mode of the system and correspondingcontrol information such that the modules perform correspondingoperations. A definable system working mode may be key image snapping, anight mode, a power saving mode, low-bandwidth transmission withcompression, a privacy information removal mode, or the like.

The control point X1 may further determine whether a local user passwordneeds to be used for encryption when data is written into the storagemodule 130. The control point X1 may further record access andoperations of a remote device for the intelligent video processingapparatus 100, to determine a device risk, find out an unauthorizedoperator after an event occurs, or the like. For an operation that maycause a system risk, the X1 control point may further determine whetherthe operation is authenticated. When necessary, the management andsecurity module 160 may be further used to perform secondaryauthentication, or an operator is required to perform manualconfirmation.

A purpose of setting the management and security module 160, thesecurity control list, and the security control points in thisembodiment of the present disclosure is to authenticate a data flowdirection of the intelligent video processing apparatus 100, anddetermine whether an operation performed by an external device on theintelligent video processing apparatus 100 or the definable intelligentcamera 200 is authenticated. These two aspects ensure data security andsystem security of the intelligent video processing apparatus 100 or thedefinable intelligent camera 200, to prevent data from flowing to anunauthorized destination address and prevent an external device fromremotely controlling the intelligent video processing apparatus 100 orthe definable intelligent camera 200 without authorization.

Functions and operations performed by several other security controlpoints in FIG. 14 are similar to those of the control point X1. A usermay perform configuration flexibly according to an actual requirement.Details are not described herein again.

To sum up, an embodiment of the present disclosure provides anintelligent video processing apparatus 100, mainly including an imageobtaining module 110, an intelligent module 120, an extension interfacea, and a communications module. The intelligent module in thisembodiment of the present disclosure not only performs an intelligentanalysis function, but also serves as a control center of the entireapparatus. A new extension module is installed on the intelligent videoprocessing apparatus using the intelligent module extension interface asrequired such that the new extension module may become a part of theapparatus. In addition, the communications module may be further used towrite various types of control information into the intelligent videoprocessing apparatus such that the intelligent video processingapparatus can implement more functions. The intelligent video processingapparatus may be combined with various front-end devices, to form anintelligent video surveillance system that can adapt to requirements ofdifferent scenarios.

On a basis of the intelligent video processing apparatus, an embodimentof the present disclosure further provides a definable intelligentcamera. The extensible intelligent camera integrates the foregoingintelligent video processing apparatus in a camera, and a front-endmodule for video collection is added, and provides functions of theforegoing intelligent video processing apparatus. According torequirements of different applications, corresponding applications canbe developed, and extension modules can be added, to improve a computingcapability of the intelligent camera.

To be specific, the intelligent video processing apparatus and thedefinable intelligent camera in the embodiments of the presentdisclosure provide an open platform such that a hardware manufacturerdoes not need to develop custom intelligent cameras for differentscenarios or different application requirements, but only needs to focuson development of corresponding software. The corresponding software maybe written into the intelligent video processing apparatus or thedefinable intelligent camera. In addition, a hardware manufacturer or auser may further choose to extend a new intelligent module according toa specific protocol or standard, to further extend a computingcapability and application scenarios of the intelligent video processingapparatus and the definable intelligent camera. The intelligent videoprocessing apparatus and the definable intelligent camera provided inthe embodiments of the present disclosure improve extensibility ofhardware, enlarge an application scope of hardware, and reduce costs forrepeatedly developing hardware.

Although the present disclosure is described with reference to theembodiments, in a process of implementing the present disclosure thatclaims protection, persons skilled in the art may understand andimplement another variation of the disclosed embodiments by viewing theaccompanying drawings, disclosed content, and the accompanying claims.In the claims, “comprising” does not exclude another component oranother step, and “a” or “one” does not exclude a meaning of plurality.A single processor or another unit may implement several functionsenumerated in the claims. Some measures are recorded in dependent claimsthat are different from each other, but this does not mean that thesemeasures cannot be combined to produce a better effect.

Although the present disclosure is described with reference to specificfeatures and the embodiments thereof, obviously, various modificationsand combinations may be made to them without departing from the spiritand scope of the present disclosure. Correspondingly, the specificationand accompanying drawings are merely exemplary description of thepresent disclosure defined by the accompanying claims, and is consideredas any of or all modifications, variations, combinations or equivalentsthat cover the scope of the present disclosure. Obviously, a personskilled in the art can make various modifications and variations to thepresent disclosure without departing from the spirit and scope of thepresent disclosure. The present disclosure is intended to cover thesemodifications and variations provided that they fall within the scope ofprotection defined by the following claims and their equivalenttechnologies.

1. A camera comprising: an image obtaining system comprising a lens anda sensor, and configured to obtain an image or video data; at least onetype of embedded processor coupled to the image obtaining system andconfigured to perform intelligent analysis and processing on the imageor the video data, wherein the at least one type of embedded processorcomprises a central processing unit (CPU), a digital signal processor(DSP), an application-specific integrated circuit (ASIC), or afield-programmable gate array (FPGA); and a communications interfacecoupled to the at least one type of embedded processor and configuredto: receive, from an external device, configuration information; andsend the configuration information to a target embedded processor of theat least one type of embedded processor according to a requirement of anapplication scenario, wherein configuration information is configured tobe modified according to the requirement, and wherein the configurationinformation extends a function of the camera and comprises at least oneof: a deep learning-based neural network model; location topologyinformation and control information for multi-camera cooperation; asecurity control list; or a control action indication.
 2. The camera ofclaim 1, wherein the communications interface is a wirelesscommunications interface.
 3. The camera of claim 1, further comprising asecurity and management system coupled to the communications interfaceand configured to: manage data and system security of the camera bysetting a security control point in a data transmission path of thecamera to perform authentication on transmitted data; and store thesecurity control list comprising a management list of the camera forexternal devices and comprising information about the external devicesallowed to access system data of the camera.
 4. The camera of claim 1,wherein the communications interface comprises an extension interface,and wherein the extension interface is configured to: couple anextension device to the camera, wherein the extension device comprisesan algorithm code according to the requirement; and implementcommunication between the at least one type of embedded processor andthe extension device.
 5. The camera of claim 4, wherein the camera isconfigured to: authorize the extension device; and use the extensiondevice as a node to control another extension device.
 6. The camera ofclaim 4, further comprising a software system configured to install asoftware driver of the extension device to manage the extension device.7. The camera of claim 4, wherein the extension device is acommunications interface, a storage device, or an intelligent processor.8. The camera of claim 4, wherein the extension interface is configuredto implement communication between the camera and the extension deviceusing a Transmission Control Protocol (TCP)/Internet Protocol (IP)communication technology or a User Datagram Protocol (UDP) technology.9. The camera of claim 4, wherein the extension interface is furtherconfigured to implement communication between the camera and theextension device using a wireless communications technology, and whereinthe wireless communications technology comprises a Wi-Fi technology, aZIGBEE technology, or a BLUETOOTH technology.
 10. A camera operatingmethod applied to a camera comprising an image obtaining system, atleast one type of embedded processor, and a communications interface,wherein the camera operating method comprises: generating, by the imageobtaining system, an image or video data; performing, by the at leastone type of embedded processor coupled to the image obtaining system,intelligent analysis and processing on the image or the video data,wherein the at least one type of embedded processor comprises a centralprocessing unit (CPU), a digital signal processor (DSP), anapplication-specific integrated circuit (ASIC), or a field-programmablegate array (FPGA); receiving, by the communications interface coupled tothe at least one type of embedded processor, configuration informationfrom an external device and sending the configuration information to atarget embedded processor of the at least one type of embedded processoraccording to a requirement of an application scenario, wherein theconfiguration information is configured to be modified according to therequirement, and wherein the configuration information extends afunction of the camera, and comprises at least one of: a deeplearning-based neural network model; location topology information andcontrol information for multi-camera cooperation; a security controllist; or a control action indication.
 11. The camera operating method ofclaim 10, wherein the communications interface is a wirelesscommunications interface.
 12. The camera operating method of claim 10,wherein the communications interface is a fixed communicationsinterface.
 13. The camera operating method of claim 10, furthercomprising: managing, by a security and management system of the camera,data and system security of the camera by setting a security controlpoint in a data transmission path of the camera to performauthentication on transmitted data; and storing, by the security andmanagement system, the security control list comprising a managementlist of the camera for external devices and comprising information aboutthe external devices allowed to access system data of the camera. 14.The camera operating method of claim 10, further comprising: coupling,by an extension interface comprised in the communications interface, anextension device to the camera, wherein the extension device comprisesan algorithm code according to the requirement; and implementing, by theextension interface, communication between the camera and the extensiondevice.
 15. The camera operating method of claim 14, further comprisingconstructing the extension device to be authorized by the camera. 16.The camera operating method of claim 14, wherein the extension device isa communications interface, a storage device, or an intelligentprocessor.
 17. The camera operating method of claim 14, furthercomprising implementing, by the extension interface, communicationbetween the camera and the extension device using a Transmission ControlProtocol (TCP)/Internet Protocol (IP) communication technology. 18.-20.(canceled)
 21. A computer program product comprising computer-executableinstructions that are stored on a non-transitory computer readablestorage medium and that, when executed by a processor, cause a camerato: generate, by an image obtaining system, an image or video data,wherein the camera comprises the image obtaining system, at least onetype of embedded processor, and a communications interface; perform, bythe at least one type of embedded processor coupled to the imageobtaining system, intelligent analysis and processing on the image orthe video data, wherein the at least one type of embedded processorcomprises a central processing unit (CPU), a digital signal processor(DSP), an application-specific integrated circuit (ASIC), or afield-programmable gate array (FPGA); receive, by the communicationsinterface coupled to the at least one type of embedded processor,configuration information from an external device and send theconfiguration information to a target embedded processor of the at leastone type of embedded processor according to a requirement of anapplication scenario, wherein the configuration information isconfigured to be modified according to the requirement, and wherein theconfiguration information extends a function of the camera and comprisesat least one of: a deep learning-based neural network model; locationtopology information and control information for multi-cameracooperation; a security control list; or a control action indication.22. The computer program product of claim 21, wherein the communicationsinterface is a wireless communications interface.
 23. The computerprogram product of claim 21, wherein the communications interface is afixed communications interface.